代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/277192/10655209
makefile
# Copyright (c) 1994, 1995, 1996
# The Regents of the University of California. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are
www.eeworm.com/read/421949/10676542
m contents.m
% Bayes Classification.
%
% bayeserr - Computes the Bayesian risk for optimal classifier.
% bayescln - Classifier based on Bayes decision rule for Gaussians.
% bayesnd - Discrim. function, dic
www.eeworm.com/read/421949/10676550
m bayesdemo1.m
% BAYESDEMO1 demo how to display discriminat function for Bayes classifier.
% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cm
www.eeworm.com/read/421856/10692293
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/349916/10783544
cpp scs.cpp
/****************************************************************************/
/* 基本遗传学习分类系统 SCS.CPP */
/* A Simple Classifier System based on G
www.eeworm.com/read/418695/10935196
m prex3.m
%PREX3 PRTOOLS example of multi-class classifier plot
help prex3
echo on
global GRIDSIZE
gs = GRIDSIZE;
GRIDSIZE = 100;
% generate 2 x 2 normal distributed classes
a = +gendath(20); % data only
www.eeworm.com/read/418695/10935201
m parzen_map.m
%PARZEN_MAP Map a dataset on a Parzen densities based classifier
%
% F = parzen_map(A,W)
%
% Maps the dataset A by the Parzen density based classfier W. F*sigm
% are the posterior probabilities. W
www.eeworm.com/read/418695/10935229
m nmc.m
%NMC Nearest Mean Classifier
%
% W = nmc(A)
%
% Computation of the nearest mean classifier between the classes in
% the dataset A.
%
% See also datasets, mappings, nmsc, ldc, fisherc, qdc, udc
www.eeworm.com/read/418695/10935495
m prex4.m
%PREX4 PRTOOLS example of classifier combining
help prex4
echo on
A = gendatd(100,100,10);
[B,C] = gendat(A,20);
wkl = klm(B,0.95); % find KL mapping input space
bkl = B*wkl; % map training
www.eeworm.com/read/417741/10977074
java testnaivebayes.java
package ir.classifiers;
import java.util.*;
/**
* Wrapper class to test NaiveBayes classifier using 10-fold CV.
* Running it with -debug option gives very detailed output
*
* @author Sugat